subject:(Energy optimization)

Texas A&M University

1. Song, Haneol. Developing a Framework for Ammonia Energy Carrier Supply Chain Optimization Incorporating Renewable Production Technologies.

Degree: MS, Energy, 2018, Texas A&M University

URL: http://hdl.handle.net/1969.1/174134

► An optimization-based supply chain management framework for statewide analyses of renewable ammonia production to electricity generation systems for Texas. With optimized renewable ammonia production plants… (more)

Subjects/Keywords: energy; optimization; ammonia

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APA (6^th Edition):

Song, H. (2018). Developing a Framework for Ammonia Energy Carrier Supply Chain Optimization Incorporating Renewable Production Technologies. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/174134

Chicago Manual of Style (16^th Edition):

Song, Haneol. “Developing a Framework for Ammonia Energy Carrier Supply Chain Optimization Incorporating Renewable Production Technologies.” 2018. Masters Thesis, Texas A&M University. Accessed January 24, 2021. http://hdl.handle.net/1969.1/174134.

MLA Handbook (7^th Edition):

Song, Haneol. “Developing a Framework for Ammonia Energy Carrier Supply Chain Optimization Incorporating Renewable Production Technologies.” 2018. Web. 24 Jan 2021.

Vancouver:

Song H. Developing a Framework for Ammonia Energy Carrier Supply Chain Optimization Incorporating Renewable Production Technologies. [Internet] [Masters thesis]. Texas A&M University; 2018. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/1969.1/174134.

Council of Science Editors:

Song H. Developing a Framework for Ammonia Energy Carrier Supply Chain Optimization Incorporating Renewable Production Technologies. [Masters Thesis]. Texas A&M University; 2018. Available from: http://hdl.handle.net/1969.1/174134

Delft University of Technology

2. Murali, Vishal (author). Inventory and Modelling of Different Objective Functions and their Impact on Optimal Design of an Offshore Wind Farm.

Degree: 2018, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:2694dcb5-292f-41e2-a9f7-e79b0dccc8c0

► The design of an offshore wind farm (OWF) is multidisciplinary in nature as it involves the design of many disciplines such as the wake effects,… (more)

▼ The design of an offshore wind farm (OWF) is multidisciplinary in nature as it involves the design of many disciplines such as the wake effects, support structure, electrical cables etc. For the optimal design of an OWF, an optimization procedure is required where all the disciplines are optimized simultaneously. The objective function plays a significant role in optimization as it expresses the main aim of the model which is to be either minimized or maximized. So far, cost of energy (COE) and annual energy production (AEP) are one of the commonly used objective functions for OWF optimization as far as the author is aware. However, there might be other objective functions that may influence the optimal design of an OWF as well. This may include maximizing the profit, minimizing the environmental impact, reducing their carbon emissions etc. Hence, this thesis investigates the overview of different objective functions and understand its impact on the optimal design of an OWF. An inventory of different objective functions is prepared, and relevant ones are selected for further study. It is observed that even though some objectives are dissimilar, they still depend on the same wind farm parameters and are therefore expected to give similar design results. From the list of objective functions, net present value (NPV) and risk management objectives are chosen for further research. The selected objective functions are then formulated in a metric for optimization. The price of electricity plays a significant role in determining the NPV. It is learnt that electricity price varies with the power supply depending on the site conditions. The electricity price is low if the supply of power is high in a region where there are many OWF’s and vice versa. Moreover, OWF investors value constant power output without any fluctuations. Hence, taking all these aspects into consideration, the electricity price in the NPV function is modelled for a constant value, wind variability and wind power predictability. The risk management function, on the other hand, aims at minimizing the uncertainty associated with an OWF project. The risk here refers to the uncertainty associated with the profit obtained from the OWF. A set of annual average wind speeds is computed using monte carlo simulations and the AEP and NPV are estimated. The mean( NPV_mean) and standard deviation ( NPV_std ) of NPV are then calculated. NPV_std represents the uncertainty in this scenario and is minimized to reduce the risk. A suitable method is then identified to deal with multiple objectives. The NPV function is maximized for maximum profit and this objective is evaluated using a single objective optimization technique. The risk management objective involves the calculation of NPV_mean and NPV_std. Both objectives are contrasting in nature as a significant reduction in NPV_std corresponds to an undesirable reduction in NPV_mean. A tradeoff between both these objectives is the best possible solution. Therefore, a multi- objective… Advisors/Committee Members: Watson, Simon (graduation committee), Zaayer, Michiel (mentor), Langelaar, Matthijs (graduation committee), Delft University of Technology (degree granting institution).

Subjects/Keywords: Wind Energy; Optimization; wind farm optimization

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APA (6^th Edition):

Murali, V. (. (2018). Inventory and Modelling of Different Objective Functions and their Impact on Optimal Design of an Offshore Wind Farm. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:2694dcb5-292f-41e2-a9f7-e79b0dccc8c0

Chicago Manual of Style (16^th Edition):

Murali, Vishal (author). “Inventory and Modelling of Different Objective Functions and their Impact on Optimal Design of an Offshore Wind Farm.” 2018. Masters Thesis, Delft University of Technology. Accessed January 24, 2021. http://resolver.tudelft.nl/uuid:2694dcb5-292f-41e2-a9f7-e79b0dccc8c0.

MLA Handbook (7^th Edition):

Murali, Vishal (author). “Inventory and Modelling of Different Objective Functions and their Impact on Optimal Design of an Offshore Wind Farm.” 2018. Web. 24 Jan 2021.

Vancouver:

Murali V(. Inventory and Modelling of Different Objective Functions and their Impact on Optimal Design of an Offshore Wind Farm. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 Jan 24]. Available from: http://resolver.tudelft.nl/uuid:2694dcb5-292f-41e2-a9f7-e79b0dccc8c0.

Council of Science Editors:

Murali V(. Inventory and Modelling of Different Objective Functions and their Impact on Optimal Design of an Offshore Wind Farm. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:2694dcb5-292f-41e2-a9f7-e79b0dccc8c0

Penn State University

3. Cheruvu, Ramya. Optimization of Power Generation in Airborne Wind Energy Systems.

Degree: 2015, Penn State University

URL: https://submit-etda.libraries.psu.edu/catalog/25105

► Optimization of power generation is important for Airborne Wind Energy Systems to increase their cost effectiveness and hence industry viability. In this thesis, an approach… (more)

Subjects/Keywords: airborne wind energy systems; optimization

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APA (6^th Edition):

Cheruvu, R. (2015). Optimization of Power Generation in Airborne Wind Energy Systems. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/25105

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Cheruvu, Ramya. “Optimization of Power Generation in Airborne Wind Energy Systems.” 2015. Thesis, Penn State University. Accessed January 24, 2021. https://submit-etda.libraries.psu.edu/catalog/25105.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Cheruvu, Ramya. “Optimization of Power Generation in Airborne Wind Energy Systems.” 2015. Web. 24 Jan 2021.

Vancouver:

Cheruvu R. Optimization of Power Generation in Airborne Wind Energy Systems. [Internet] [Thesis]. Penn State University; 2015. [cited 2021 Jan 24]. Available from: https://submit-etda.libraries.psu.edu/catalog/25105.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Cheruvu R. Optimization of Power Generation in Airborne Wind Energy Systems. [Thesis]. Penn State University; 2015. Available from: https://submit-etda.libraries.psu.edu/catalog/25105

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Ontario Institute of Technology

4. Bingham, Raymond D. Optimization of residential buildings and renewable energy integration in small island developing states: the Bahamas as a case study.

Degree: 2017, University of Ontario Institute of Technology

URL: http://hdl.handle.net/10155/847

► An optimization approach is used to assess the energy performance and design of residential homes in The Bahamas with the goal of providing objective data… (more)

Subjects/Keywords: Bahamas; Optimization; Residential; Renewable energy

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APA (6^th Edition):

Bingham, R. D. (2017). Optimization of residential buildings and renewable energy integration in small island developing states: the Bahamas as a case study. (Thesis). University of Ontario Institute of Technology. Retrieved from http://hdl.handle.net/10155/847

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Bingham, Raymond D. “Optimization of residential buildings and renewable energy integration in small island developing states: the Bahamas as a case study.” 2017. Thesis, University of Ontario Institute of Technology. Accessed January 24, 2021. http://hdl.handle.net/10155/847.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Bingham, Raymond D. “Optimization of residential buildings and renewable energy integration in small island developing states: the Bahamas as a case study.” 2017. Web. 24 Jan 2021.

Vancouver:

Bingham RD. Optimization of residential buildings and renewable energy integration in small island developing states: the Bahamas as a case study. [Internet] [Thesis]. University of Ontario Institute of Technology; 2017. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/10155/847.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Bingham RD. Optimization of residential buildings and renewable energy integration in small island developing states: the Bahamas as a case study. [Thesis]. University of Ontario Institute of Technology; 2017. Available from: http://hdl.handle.net/10155/847

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Miami

5. Lee, Hoe-Gil. Optimal Design of Solar Photovoltaic Systems.

Degree: PhD, Mechanical Engineering (Engineering), 2015, University of Miami

URL: https://scholarlyrepository.miami.edu/oa_dissertations/1452

► A solar PV array system is comprised of the following components - solar cells, panel modules, and an array system. Thus, overall optimal design of… (more)

▼ A solar PV array system is comprised of the following components - solar cells, panel modules, and an array system. Thus, overall optimal design of a solar PV system involves the optimal design of the components at three levels - solar cell, panel module, and array. The conversion efficiency, power output, and incident solar energy pertaining to the requirements of seasonal demands are to be considered in the process. At the solar cell level, cell performance depends on solar cell structure, top contact design, and cell size. The correlations between cell structure, cell size and top contact design are investigated. At the PV panel module level, the optimization of a PV panel module is investigated based on the optimal design of individual solar cells for maximizing the power output. The role of the PV panel module is interactive between solar cells and the array system and is composed of a number of solar cells and panel modules. In designing a solar PV array system with cost considerations, the performance of a solar PV array system is investigated based on the performance of its subsystems - the solar cell and the panel module – as well as the cost of the array system. The optimal design of an array system is considered by formulating six single-objective optimization problems – the maximization of the conversion efficiency of the cells, power output of the arrays, annual monthly average incident solar energy, lowest month’s and highest month’s incident solar energy and minimization of cost. Multi-objective optimum designs of a solar cell, flat plate solar PV array system and compound parabolic concentrator (CPC) PV collector system are also considered by using mathematical techniques. Game theory and fuzzy set theory methodologies are used for finding the solution of multi-objective optimization problems derived from the results of single-objective problems using genetic algorithms of ga (program MATLAB). For a solar cell, the multi-objective optimization is constructed using two objectives – the maximization of the conversion efficiency and power output. The resulting multi-objective optimization (of a solar cell) is investigated with varying intensities of sunlight and by placing constraints on the minimum permissible conversion efficiency while maximizing efficiency and power output. Multilevel system optimization problems are solved using game theory and fuzzy set theory for finding a compromise solution of the six-objective optimization problems which are related to conversion efficiency, power output, annual incident solar energy, winter incident solar energy, summer incident solar energy and total cost of the PV array system. In the case of a solar CPC collector system, there are three single-objective problems: annual monthly average of incident solar energy, lowest month’s incident solar energy and cost. Game theory methodology is used for finding a compromise solution in the process of constraints stated. The aim of uncertainty analysis is to predict the performance of a component or system in the… Advisors/Committee Members: Sigiresu S. Rao, Shihab S. Asfour, Michael R. Swain, Hongtan Liu.

Subjects/Keywords: solar energy; photovoltaic; optimization

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APA (6^th Edition):

Lee, H. (2015). Optimal Design of Solar Photovoltaic Systems. (Doctoral Dissertation). University of Miami. Retrieved from https://scholarlyrepository.miami.edu/oa_dissertations/1452

Chicago Manual of Style (16^th Edition):

Lee, Hoe-Gil. “Optimal Design of Solar Photovoltaic Systems.” 2015. Doctoral Dissertation, University of Miami. Accessed January 24, 2021. https://scholarlyrepository.miami.edu/oa_dissertations/1452.

MLA Handbook (7^th Edition):

Lee, Hoe-Gil. “Optimal Design of Solar Photovoltaic Systems.” 2015. Web. 24 Jan 2021.

Vancouver:

Lee H. Optimal Design of Solar Photovoltaic Systems. [Internet] [Doctoral dissertation]. University of Miami; 2015. [cited 2021 Jan 24]. Available from: https://scholarlyrepository.miami.edu/oa_dissertations/1452.

Council of Science Editors:

Lee H. Optimal Design of Solar Photovoltaic Systems. [Doctoral Dissertation]. University of Miami; 2015. Available from: https://scholarlyrepository.miami.edu/oa_dissertations/1452

University of Manitoba

6. Bagheri, Shahriar. Piezoelectric energy harvesting: modeling, optimization, and experimental study of transient charging behavior.

Degree: Mechanical Engineering, 2019, University of Manitoba

URL: http://hdl.handle.net/1993/34085

► Piezoelectric Energy Harvesters (PEH) are complex dynamic electromechanical systems. As such, derivation of an accurate model that can describe system's behavior under different operating conditions… (more)

▼ Piezoelectric Energy Harvesters (PEH) are complex dynamic electromechanical systems. As such, derivation of an accurate model that can describe system's behavior under different operating conditions is challenging. Moreover, the interconnection between the piezoelectric transducer and any forms of power conditioning and storage further complicates the modeling process. This thesis tackles the problem of modeling the transient operation of a PEH during the charging process of an external storage device through electrical interfacing circuits. A semi-theoretical model is proposed based on the Euler-Bernoulli beam theory. The model takes into account the electromechanical coupling effects of the piezoelectric material, as well as the dynamic process of charging an external storage capacitor. The effects of an standard interfacing circuit with diode bridge rectifier and a non-linear synchronous switching circuit on the transient charging dynamics are modeled and comprehensively studied. Additionally, an experimental test setup is developed to validate the efficacy of the developed model and to further investigate the effect of different interfacing circuits on the energy harvesting system. Furthermore, the problem of finding the optimal design parameters for a PEH is considered. A new simulation-based optimization procedure is proposed with the goal of acquiring the optimal geometric and circuit design parameters that lead to higher energy harvesting efficiency and also enhance the obtained electrical power. The basis of the optimization platform is the developed semi-theoretical model of the energy harvesting system. In order to avoid the time and space (memory) complexities during the computer optimization caused by the expensive-to-evaluate Objective Function (OF) (i.e. simulation model) combination of Artificial Intelligence (AI) and Evolutionary Algorithm (EA) is used to facilitate the optimization process, while maintaining the required accuracy. More precisely, a computationally efficient Neural Network (NN) model is first trained based on a set of training data obtained from the simulation model. Performance and accuracy of the NN training is studied using available statistical methods. Second, a Genetic Algorithm (GA) optimization performs a block-box optimization procedure, using the trained NN model for OF evaluation. Finally a thorough analysis of the optimal design parameters obtained from the optimization process is provided. Advisors/Committee Members: Wu, Nan (Mechanical Engineering), Ojo, Olanrewaju (Mechanical Engineering).

Subjects/Keywords: Energy harvesting; Piezoelectric; Modeling; Optimization

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APA (6^th Edition):

Bagheri, S. (2019). Piezoelectric energy harvesting: modeling, optimization, and experimental study of transient charging behavior. (Thesis). University of Manitoba. Retrieved from http://hdl.handle.net/1993/34085

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Bagheri, Shahriar. “Piezoelectric energy harvesting: modeling, optimization, and experimental study of transient charging behavior.” 2019. Thesis, University of Manitoba. Accessed January 24, 2021. http://hdl.handle.net/1993/34085.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Bagheri, Shahriar. “Piezoelectric energy harvesting: modeling, optimization, and experimental study of transient charging behavior.” 2019. Web. 24 Jan 2021.

Vancouver:

Bagheri S. Piezoelectric energy harvesting: modeling, optimization, and experimental study of transient charging behavior. [Internet] [Thesis]. University of Manitoba; 2019. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/1993/34085.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Bagheri S. Piezoelectric energy harvesting: modeling, optimization, and experimental study of transient charging behavior. [Thesis]. University of Manitoba; 2019. Available from: http://hdl.handle.net/1993/34085

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Delft University of Technology

7. Van Nielen, S.S. (author). Techno-economic Assessment of Solid Oxide Fuel Cells and Fuel-assisted Electrolysis Cells in Future Energy Systems.

Degree: 2016, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:7abfaebc-5975-4707-b4f2-f7082500f397

► The Master's programme Industrial Ecology is jointly organised by Leiden University and Delft University of Technology - There is an increasing awareness in society of… (more)

▼ The Master's programme Industrial Ecology is jointly organised by Leiden University and Delft University of Technology - There is an increasing awareness in society of the problems and risks associated with climate change. In response, a transition from fossil to renewable energy sources is taking place. Meanwhile, there is an ongoing trend of increasing electricity demand for various applications. There is a growing number of electric appliances, as well as the electrification of heating, cooling, and transportation services. These changes provide a challenge when it comes to matching electricity production and consumption. The intermittent nature of wind and solar energy, combined with the large loads of heat pumps and BEVs, reduces the flexibility and robustness of the system in the future. Solid oxide cells (SOCs) can contribute to solving the balancing problem of the electricity grid. SOCs perform electrochemical conversions and are developed for decentral energy conversion applications. A solid oxide fuel cell (SOFC) uses a fuel to produce electricity, hydrogen, and heat. Solid oxide fuel-assisted electrolysis cells (SOFECs) consume electricity and a fuel while producing hydrogen and heat. Gaseous fuels like natural gas, hydrogen, and biogas can be used. SOFCs have been under investigation for decades, and are mainly applied as backup power source. SOFEC technology, on the other hand, is rather unknown. Only a dozen of articles has been published, dedicated to theoretical models and small-scale lab tests. These SOCs are seen as promising technologies, because of the high energy efficiency, flexible operation, and ability to produce hydrogen. The aim of this research is to assess whether it is feasible to introduce SOFCs and SOFECs in the (future) Dutch energy system. This research takes a broad perspective, by assessing the technological components in relation to the energy system as a whole. In addition, multiple aspects that determine the feasibility are assessed. These aspects are the technical possibilities and limitations of SOCs, their cost-effectiveness under different assumptions, the environmental implications, and societal drivers and barriers for the introduction in niche markets. Existing literature shows that the commercial competitiveness of SOCs is currently limited because of high investment costs and a limited lifetime. The manufacturing costs can be decreased by learning through research and development, and higher production volumes. To prolong the service life, degradation of the electrodes at microscopic level should be minimised. Recent research indicates that regular switching between fuel cell and (fuel assisted) electrolysis mode can also prevent degradation. It is therefore recommended to further investigate how the service life is prolonged for a SOFC that is operated regularly as SOFEC. A thermodynamic 1-D cell model was used to describe the inputs and outputs of a SOFC and a SOFEC. Based on this model, non-linear sets of equations with two degrees of freedom were derived for both… Advisors/Committee Members: Hemmes, K. (mentor), Ramírez-Elizondo, L.M. (mentor).

Subjects/Keywords: Energy system optimization; SOFC; SOFEC

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APA (6^th Edition):

Van Nielen, S. S. (. (2016). Techno-economic Assessment of Solid Oxide Fuel Cells and Fuel-assisted Electrolysis Cells in Future Energy Systems. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:7abfaebc-5975-4707-b4f2-f7082500f397

Chicago Manual of Style (16^th Edition):

Van Nielen, S S (author). “Techno-economic Assessment of Solid Oxide Fuel Cells and Fuel-assisted Electrolysis Cells in Future Energy Systems.” 2016. Masters Thesis, Delft University of Technology. Accessed January 24, 2021. http://resolver.tudelft.nl/uuid:7abfaebc-5975-4707-b4f2-f7082500f397.

MLA Handbook (7^th Edition):

Van Nielen, S S (author). “Techno-economic Assessment of Solid Oxide Fuel Cells and Fuel-assisted Electrolysis Cells in Future Energy Systems.” 2016. Web. 24 Jan 2021.

Vancouver:

Van Nielen SS(. Techno-economic Assessment of Solid Oxide Fuel Cells and Fuel-assisted Electrolysis Cells in Future Energy Systems. [Internet] [Masters thesis]. Delft University of Technology; 2016. [cited 2021 Jan 24]. Available from: http://resolver.tudelft.nl/uuid:7abfaebc-5975-4707-b4f2-f7082500f397.

Council of Science Editors:

Van Nielen SS(. Techno-economic Assessment of Solid Oxide Fuel Cells and Fuel-assisted Electrolysis Cells in Future Energy Systems. [Masters Thesis]. Delft University of Technology; 2016. Available from: http://resolver.tudelft.nl/uuid:7abfaebc-5975-4707-b4f2-f7082500f397

University of Illinois – Urbana-Champaign

8. Buccafusca, Lucas D. Modeling and maximizing power in wind turbine arrays.

Degree: MS, Electrical & Computer Engr, 2017, University of Illinois – Urbana-Champaign

URL: http://hdl.handle.net/2142/99123

► This work considers a specific application domain, that of wind turbine arrays, and explores algorithms for determining individual axial induction factors that optimize overall energy… (more)

Subjects/Keywords: Optimization; Wind energy; Dynamic programming

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APA (6^th Edition):

Buccafusca, L. D. (2017). Modeling and maximizing power in wind turbine arrays. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/99123

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Buccafusca, Lucas D. “Modeling and maximizing power in wind turbine arrays.” 2017. Thesis, University of Illinois – Urbana-Champaign. Accessed January 24, 2021. http://hdl.handle.net/2142/99123.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Buccafusca, Lucas D. “Modeling and maximizing power in wind turbine arrays.” 2017. Web. 24 Jan 2021.

Vancouver:

Buccafusca LD. Modeling and maximizing power in wind turbine arrays. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2017. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2142/99123.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Buccafusca LD. Modeling and maximizing power in wind turbine arrays. [Thesis]. University of Illinois – Urbana-Champaign; 2017. Available from: http://hdl.handle.net/2142/99123

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Waterloo

9. Doroshenko, Mykhailo. Quantifying the Effects of Solar Panel Orientation on the Electrical Grid.

Degree: 2016, University of Waterloo

URL: http://hdl.handle.net/10012/11066

► As the prices of solar panels continue to decline, energy production from solar farms is skyrocketing, leading to a situation where, at certain times, solar… (more)

Subjects/Keywords: renewable energy; solar power; optimization

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APA (6^th Edition):

Doroshenko, M. (2016). Quantifying the Effects of Solar Panel Orientation on the Electrical Grid. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/11066

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Doroshenko, Mykhailo. “Quantifying the Effects of Solar Panel Orientation on the Electrical Grid.” 2016. Thesis, University of Waterloo. Accessed January 24, 2021. http://hdl.handle.net/10012/11066.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Doroshenko, Mykhailo. “Quantifying the Effects of Solar Panel Orientation on the Electrical Grid.” 2016. Web. 24 Jan 2021.

Vancouver:

Doroshenko M. Quantifying the Effects of Solar Panel Orientation on the Electrical Grid. [Internet] [Thesis]. University of Waterloo; 2016. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/10012/11066.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Doroshenko M. Quantifying the Effects of Solar Panel Orientation on the Electrical Grid. [Thesis]. University of Waterloo; 2016. Available from: http://hdl.handle.net/10012/11066

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Sydney

10. Zhang, Yongxi. POWER SYSTEM OPERATION AND PLANNING WITH RENEWABLE POWER GENERATIONS AND ENERGY STORAGE .

Degree: 2016, University of Sydney

URL: http://hdl.handle.net/2123/15974

► Renewable energy, especially wind, photovoltaic technologies and battery energy storage (BES) have become emerging technologies over recent years with the increasing prevalence of the smart… (more)

▼ Renewable energy, especially wind, photovoltaic technologies and battery energy storage (BES) have become emerging technologies over recent years with the increasing prevalence of the smart grid. Recently, the penetration level of renewable energy has become an area of focus motivated by growing environmental and economic concerns. Integrating renewable energy resources offers various advantages in reducing carbon dioxide emission, increasing energy efficiency and enhancing system flexibility and reliability. At the same time, the stochastic nature of renewable energy also challenges the grid in aspects of system scheduling and planning. In order to effectively accommodate various renewable energy technologies and storage systems into the smart grid, it is vital for system operators, and utility owners to find appropriate strategies for power system operation and planning. Aiming to address the main issues arising from renewable energy integration, this research explores study areas that focus on operation and planning for better integration of emerging renewable energy resource technologies. Specifically, for the planning aspect, this thesis addresses how to optimally allocate an Energy Storage System (ESS) in distribution networks; for the operational aspect, this thesis discusses how to optimally dispatch wind power in a transmission system, respectively. In the area of long-term ESS expansion planning in active distribution networks (ADN), this thesis developed some methods for battery energy storage system (BESS) allocation with abundant renewable energy resources. ESSs are commonly applied to cooperate with renewable power generation to manage uncertainty and randomness, especially in distribution networks. Particularly, a chance constrained programming based planning framework was presented to determine the appropriate planning solution for battery units to reduce wind power curtailment. The trade-off between total cost, and wind power utilization level was analysed under different confidence levels. Furthermore, to study the potential voltage regulation effects of BESS in ADN with sufficient renewable energy resources, a stochastic BESS allocation scheme was developed which took conservation voltage reduction effects into consideration. Also, the stochastic factor of load composition is simulated using scenario analysis. Moreover, in order to fully analyse the role that BES units play in voltage regulation, a novel methodology was established to address voltage rise issues. The sparse theory is incorporated in the problem formulation. This model aims to build a fully distributed control scheme for voltage regulation in ADN using dispersed BES units. In the area of short-term operation, a stochastic optimal dispatch model of a power system considering interactions of multiple wind farm outputs was established at first. The fat-tail relevance among multiple wind farm output power was simulated utilizing the Gumbel-copula function. A chance constraints embedded stochastic optimal dispatch was then proposed for…

Subjects/Keywords: renewable energy; planning; operation; optimization

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APA (6^th Edition):

Zhang, Y. (2016). POWER SYSTEM OPERATION AND PLANNING WITH RENEWABLE POWER GENERATIONS AND ENERGY STORAGE . (Thesis). University of Sydney. Retrieved from http://hdl.handle.net/2123/15974

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Zhang, Yongxi. “POWER SYSTEM OPERATION AND PLANNING WITH RENEWABLE POWER GENERATIONS AND ENERGY STORAGE .” 2016. Thesis, University of Sydney. Accessed January 24, 2021. http://hdl.handle.net/2123/15974.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Zhang, Yongxi. “POWER SYSTEM OPERATION AND PLANNING WITH RENEWABLE POWER GENERATIONS AND ENERGY STORAGE .” 2016. Web. 24 Jan 2021.

Vancouver:

Zhang Y. POWER SYSTEM OPERATION AND PLANNING WITH RENEWABLE POWER GENERATIONS AND ENERGY STORAGE . [Internet] [Thesis]. University of Sydney; 2016. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2123/15974.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Zhang Y. POWER SYSTEM OPERATION AND PLANNING WITH RENEWABLE POWER GENERATIONS AND ENERGY STORAGE . [Thesis]. University of Sydney; 2016. Available from: http://hdl.handle.net/2123/15974

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Texas – Austin

11. James, Corey Matthew, 1976-. Reducing the cost of operational water on military bases through modeling, optimization, and control.

Degree: PhD, Chemical Engineering, 2017, University of Texas – Austin

URL: http://hdl.handle.net/2152/62970

► Military municipal water systems provide safe and clean water to the surrounding community while also supporting the intense and often unpredictable training schedules of the… (more)

▼ Military municipal water systems provide safe and clean water to the surrounding community while also supporting the intense and often unpredictable training schedules of the tenant units. Much like their civilian counterparts, military water systems are also consumers of great amounts of energy and capital. As a part of the Army Net Zero program in 2011, an annual water inventory conducted on eight U.S. Army installations concluded that consumption was 5.5 billion gallons. Using the Environmental Protection Agency’s average national estimate of 1,500 kWh of energy consumed for every 1,000 gallons of treated water, it is readily apparent that the department of defense is a heavy consumer of both water and energy. Because the scale of the military’s usage is so vast, so too is their waste. Waste in water systems is common and commonly neglected, as many were initially constructed decades ago and the commodity that they transport is relatively inexpensive. However, recent droughts affecting regions of the United States highlighted the need to conserve and avoid waste, regardless of the commodity price. The efficiency of water systems is highly dependent upon developing accurate models and using those models to accurately deal with disturbances such as demand and chlorine concentration. This work extends water distribution system modeling, optimization, and control to a military setting where constraints are tighter for resiliency purposes, demands are often unpredictable, and saving money and water improves defense capabilities. First, a discretized nonlinear, equation based model of a known system at an existing U.S. Army installation that accurately predicts system behavior under typical demand considerations. The model is calibrated for accuracy using actual system data from a military installation and employed in a nonlinear optimization program to study reduction of costs, minimizing waste, and improvements in energy efficiency. Demand profiles were constructed from residential data and scaled to better represent demand on military bases. With very little adjustment, this model can be used to optimize similar systems in the military inventory. Water and energy savings exceed 10% in the optimized system, which predicts the Army could save greater than $1.5 million per year in the continental United States if rigorous optimization was conducted on storage and pumping at every base. It is shown that a reduced order empirical model is a viable alternative to the computationally expensive equation based approach. The empirical model is used to implement model predictive control, providing the system protection against large and unpredictable disturbances. This method adds an additional manipulated variable, chlorine injection, to ensure efficient constraint compliance. Experimental results show this method further supports the aforementioned savings in the optimized system alone, while efficiently handling disturbances. This research closes previous gaps in research, particularly on military installations. First,… Advisors/Committee Members: Edgar, Thomas F. (advisor), Webber, Michael E., 1971- (advisor), Rochelle, Gary T (committee member), Baldea, Michael (committee member), Werth, Charles J (committee member).

Subjects/Keywords: Control; Optimization; Water; Energy; Military

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APA (6^th Edition):

James, Corey Matthew, 1. (2017). Reducing the cost of operational water on military bases through modeling, optimization, and control. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/62970

Chicago Manual of Style (16^th Edition):

James, Corey Matthew, 1976-. “Reducing the cost of operational water on military bases through modeling, optimization, and control.” 2017. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/62970.

MLA Handbook (7^th Edition):

James, Corey Matthew, 1976-. “Reducing the cost of operational water on military bases through modeling, optimization, and control.” 2017. Web. 24 Jan 2021.

Vancouver:

James, Corey Matthew 1. Reducing the cost of operational water on military bases through modeling, optimization, and control. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2017. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/62970.

Council of Science Editors:

James, Corey Matthew 1. Reducing the cost of operational water on military bases through modeling, optimization, and control. [Doctoral Dissertation]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/62970

Oklahoma State University

12. Maheshwari, Zeel. Approach to Modeling and Optimization of Integrated Renewable Energy System (Ires).

Degree: Electrical Engineering, 2013, Oklahoma State University

URL: http://hdl.handle.net/11244/14981

► The purpose of this study was to cost optimize electrical part of IRES (Integrated Renewable Energy Systems) using HOMER and maximize the utilization of resources… (more)

▼ The purpose of this study was to cost optimize electrical part of IRES (Integrated Renewable Energy Systems) using HOMER and maximize the utilization of resources using MATLAB programming. IRES is an effective and a viable strategy that can be employed to harness renewable energy resources to energize remote rural areas of developing countries. The resource- need matching, which is the basis for IRES makes it possible to provide energy in an efficient and cost effective manner. Modeling and optimization of IRES for a selected study area makes IRES more advantageous when compared to hybrid concepts. A remote rural area with a population of 700 in 120 households and 450 cattle is considered as an example for cost analysis and optimization. Mathematical models for key components of IRES such as biogas generator, hydropower generator, wind turbine, PV system and battery banks are developed. A discussion of the size of water reservoir required is also presented. Modeling of IRES on the basis of need to resource and resource to need matching is pursued to help in optimum use of resources for the needs. Fixed resources such as biogas and water are used in prioritized order whereas movable resources such as wind and solar can be used simultaneously for different priorities. IRES is cost optimized for electricity demand using HOMER software that is developed by the NREL (National Renewable Energy Laboratory). HOMER optimizes configuration for electrical demand only and does not consider other demands such as biogas for cooking and water for domestic and irrigation purposes. Hence an optimization program based on the need-resource modeling of IRES is performed in MATLAB. Optimization of the utilization of resources for several needs is performed. Results obtained from MATLAB clearly show that the available resources can fulfill the demand of the rural areas. Introduction of IRES in rural communities has many socio-economic implications. It brings about improvement in living environment and community welfare by supplying the basic needs such as biogas for cooking, water for domestic and irrigation purposes and electrical energy for lighting, communication, cold storage, educational and small- scale industrial purposes. Advisors/Committee Members: Ramakumar, Rama G. (advisor), Hagan, Martin (committee member), Bukkapatnam, Satish (committee member).

Subjects/Keywords: energy; integrated; modeling; optimization; renewable

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APA (6^th Edition):

Maheshwari, Z. (2013). Approach to Modeling and Optimization of Integrated Renewable Energy System (Ires). (Thesis). Oklahoma State University. Retrieved from http://hdl.handle.net/11244/14981

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Maheshwari, Zeel. “Approach to Modeling and Optimization of Integrated Renewable Energy System (Ires).” 2013. Thesis, Oklahoma State University. Accessed January 24, 2021. http://hdl.handle.net/11244/14981.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Maheshwari, Zeel. “Approach to Modeling and Optimization of Integrated Renewable Energy System (Ires).” 2013. Web. 24 Jan 2021.

Vancouver:

Maheshwari Z. Approach to Modeling and Optimization of Integrated Renewable Energy System (Ires). [Internet] [Thesis]. Oklahoma State University; 2013. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/11244/14981.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Maheshwari Z. Approach to Modeling and Optimization of Integrated Renewable Energy System (Ires). [Thesis]. Oklahoma State University; 2013. Available from: http://hdl.handle.net/11244/14981

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Colorado State University

13. Oxley, Mark. Energy- and thermal-aware resource management for heterogeneous high-performance computing systems.

Degree: PhD, Electrical and Computer Engineering, 2016, Colorado State University

URL: http://hdl.handle.net/10217/173356

► Today's high-performance computing (HPC) systems face the issue of balancing electricity (energy) use and performance. Rising energy costs are forcing system operators to either operate… (more)

▼ Today's high-performance computing (HPC) systems face the issue of balancing electricity (energy) use and performance. Rising energy costs are forcing system operators to either operate within an energy budget or to reduce energy use as much as possible while still maintaining performance-based service agreements. Energy-aware resource management is one method for solving such problems. Resource management in the context of high-performance computing refers to the process of assigning and scheduling workloads to resources (e.g., compute nodes). Because the cooling systems in HPC facilities also consume a considerable amount of energy, it is important to consider the computer room air conditioning (CRAC) units as a controllable resource and to study the relationship (and energy consumption impact) between the computing and cooling systems. In this thesis, we present four primary contributing studies with differing environments and novel techniques designed for each of those environments. Each study proposes new ideas in the field of energy- and thermal-aware resource management for heterogeneous HPC systems. Our first contribution explores the problem of assigning a collection of independent tasks ("bag-of-tasks") to a heterogeneous HPC system in an energy-aware manner, where task execution times vary. We propose two new measures that consider these uncertainties with respect to makespan and energy: makespan-robustness and energy-robustness. We design resource management heuristics to either: (a) maximize makespan-robustness within an energy-robustness constraint, or (b) maximize energy-robustness within a makespan-robustness constraint. Our next contribution studies a rate-based environment where task execution rates are assigned to compute cores within the HPC facility. The performance measure in this study is the reward rate earned for executing tasks. We analyze the impact that co-location interference (i.e., the performance degradation experienced when tasks are simultaneously executing on cores that share memory resources) has on the reward rate. Novel heuristics are designed that maximize the reward rate under power and thermal constraints, considering the interactions between both computing and cooling systems. As part of the third contribution, we design new techniques for a geographical load distribution problem. That is, our proposed techniques intelligently distribute the workload to data centers located in different geographical regions that have varying energy prices and amount of renewable energy available. The novel techniques we propose use knowledge of co-location interference, thermal models, varying energy prices, and available renewable energy at each data center to minimize monetary energy costs while ensuring all tasks in the workload are completed. Our final contribution is a new energy- and thermal-aware runtime framework designed to maximize reward earned from completing individual tasks by their deadlines within energy and thermal constraints.… Advisors/Committee Members: Siegel, H. J. (advisor), Pasricha, Sudeep (advisor), Maciejewski, Anthony A. (committee member), Whitley, Darrell (committee member).

Subjects/Keywords: datacenter; optimization; energy; cooling

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APA (6^th Edition):

Oxley, M. (2016). Energy- and thermal-aware resource management for heterogeneous high-performance computing systems. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/173356

Chicago Manual of Style (16^th Edition):

Oxley, Mark. “Energy- and thermal-aware resource management for heterogeneous high-performance computing systems.” 2016. Doctoral Dissertation, Colorado State University. Accessed January 24, 2021. http://hdl.handle.net/10217/173356.

MLA Handbook (7^th Edition):

Oxley, Mark. “Energy- and thermal-aware resource management for heterogeneous high-performance computing systems.” 2016. Web. 24 Jan 2021.

Vancouver:

Oxley M. Energy- and thermal-aware resource management for heterogeneous high-performance computing systems. [Internet] [Doctoral dissertation]. Colorado State University; 2016. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/10217/173356.

Council of Science Editors:

Oxley M. Energy- and thermal-aware resource management for heterogeneous high-performance computing systems. [Doctoral Dissertation]. Colorado State University; 2016. Available from: http://hdl.handle.net/10217/173356

Cal Poly

14. Kim, Byungyu. Solar Energy Generation Forecasting and Power Output Optimization of Utility Scale Solar Field.

Degree: MS, Mechanical Engineering, 2020, Cal Poly

URL: https://digitalcommons.calpoly.edu/theses/2149 ; 10.15368/theses.2020.55

► The optimization of photovoltaic (PV) power generation system requires an accurate system performance model capable of validating the PV system optimization design. Currently, many… (more)

Subjects/Keywords: Solar Energy; Optimization; Backtracking

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APA (6^th Edition):

Kim, B. (2020). Solar Energy Generation Forecasting and Power Output Optimization of Utility Scale Solar Field. (Masters Thesis). Cal Poly. Retrieved from https://digitalcommons.calpoly.edu/theses/2149 ; 10.15368/theses.2020.55

Chicago Manual of Style (16^th Edition):

Kim, Byungyu. “Solar Energy Generation Forecasting and Power Output Optimization of Utility Scale Solar Field.” 2020. Masters Thesis, Cal Poly. Accessed January 24, 2021. https://digitalcommons.calpoly.edu/theses/2149 ; 10.15368/theses.2020.55.

MLA Handbook (7^th Edition):

Kim, Byungyu. “Solar Energy Generation Forecasting and Power Output Optimization of Utility Scale Solar Field.” 2020. Web. 24 Jan 2021.

Vancouver:

Kim B. Solar Energy Generation Forecasting and Power Output Optimization of Utility Scale Solar Field. [Internet] [Masters thesis]. Cal Poly; 2020. [cited 2021 Jan 24]. Available from: https://digitalcommons.calpoly.edu/theses/2149 ; 10.15368/theses.2020.55.

Council of Science Editors:

Kim B. Solar Energy Generation Forecasting and Power Output Optimization of Utility Scale Solar Field. [Masters Thesis]. Cal Poly; 2020. Available from: https://digitalcommons.calpoly.edu/theses/2149 ; 10.15368/theses.2020.55

Delft University of Technology

15. Van Staveren, R.J.M. (author). The role of electrical energy storage in a future sustainable electricity grid.

Degree: 2014, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:69942211-7216-4c09-b9e5-e5e452240a5b

►

The call for lower CO2 emissions has increased the integration of renewable energy sources in the electricity system. However, these intermittent sources do not follow… (more)

Subjects/Keywords: electrical energy storage; renewable energy; optimization

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APA (6^th Edition):

Van Staveren, R. J. M. (. (2014). The role of electrical energy storage in a future sustainable electricity grid. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:69942211-7216-4c09-b9e5-e5e452240a5b

Chicago Manual of Style (16^th Edition):

Van Staveren, R J M (author). “The role of electrical energy storage in a future sustainable electricity grid.” 2014. Masters Thesis, Delft University of Technology. Accessed January 24, 2021. http://resolver.tudelft.nl/uuid:69942211-7216-4c09-b9e5-e5e452240a5b.

MLA Handbook (7^th Edition):

Van Staveren, R J M (author). “The role of electrical energy storage in a future sustainable electricity grid.” 2014. Web. 24 Jan 2021.

Vancouver:

Van Staveren RJM(. The role of electrical energy storage in a future sustainable electricity grid. [Internet] [Masters thesis]. Delft University of Technology; 2014. [cited 2021 Jan 24]. Available from: http://resolver.tudelft.nl/uuid:69942211-7216-4c09-b9e5-e5e452240a5b.

Council of Science Editors:

Van Staveren RJM(. The role of electrical energy storage in a future sustainable electricity grid. [Masters Thesis]. Delft University of Technology; 2014. Available from: http://resolver.tudelft.nl/uuid:69942211-7216-4c09-b9e5-e5e452240a5b

University of Victoria

16. English, Jeffrey. Decarbonization pathways for the western Canadian electricity system.

Degree: Department of Mechanical Engineering, 2020, University of Victoria

URL: http://hdl.handle.net/1828/11483

► Decarbonizing the electricity system (i.e. eliminating generation from fossil fuels and replacing it with non-emitting sources) is widely considered a necessary step to limiting anthropogenic… (more)

▼ Decarbonizing the electricity system (i.e. eliminating generation from fossil fuels and replacing it with non-emitting sources) is widely considered a necessary step to limiting anthropogenic emissions and minimizing the impacts of climate change. Selecting which non-emitting generators should replace existing fossil fuel sources, and when to build them, is critical to the success of this transition. The optimal pathway to decarbonisation is highly region-specific. It is impacted by both factors such as availability of renewable resources, existing generation resources, and government policy. This dissertation presents a techno-economic model that is used to assess the decarbonisation of the combined British Columbia and Alberta electricity system. It is found that high levels of decarbonisation are possible through a combination of new wind generation, particularly in Alberta, and increased trade between Alberta, British Columbia, and the United States. Following on this finding, the variability related to high penetrations of renewable generation is introduced to the model and its impact is assessed. These results indicate that variability will be an important constraint in planning decarbonized energy systems. Finally, the representation of British Columbia’s existing hydroelectric resources is expanded to determine the ability to buffer variable renewable generation with these resources. This study finds that, while existing hydroelectric resources can support much of the variability in a highly renewable energy system, additional technologies and/or policies are needed to reach a fully zero-carbon system. The findings in this thesis show that British Columbia and Alberta, with an expanded interconnection between the provinces, can reach high penetrations of variable renewable energy. The majority of this generation consists of wind energy in Alberta, which is abundant and low-cost compared to other generation options. While comparatively little generation is added in British Columbia, the existing hydroelectric resources in the province provide significant flexibility to support the variability of this wind generation. Advisors/Committee Members: Rowe, Andrew Michael (supervisor), Wild, Peter Martin (supervisor).

Subjects/Keywords: Energy systems; Optimization; Renewable energy; Technoeconomic modelling

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APA (6^th Edition):

English, J. (2020). Decarbonization pathways for the western Canadian electricity system. (Thesis). University of Victoria. Retrieved from http://hdl.handle.net/1828/11483

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

English, Jeffrey. “Decarbonization pathways for the western Canadian electricity system.” 2020. Thesis, University of Victoria. Accessed January 24, 2021. http://hdl.handle.net/1828/11483.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

English, Jeffrey. “Decarbonization pathways for the western Canadian electricity system.” 2020. Web. 24 Jan 2021.

Vancouver:

English J. Decarbonization pathways for the western Canadian electricity system. [Internet] [Thesis]. University of Victoria; 2020. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/1828/11483.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

English J. Decarbonization pathways for the western Canadian electricity system. [Thesis]. University of Victoria; 2020. Available from: http://hdl.handle.net/1828/11483

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Ontario Institute of Technology

17. Rabbani, Hassan. Modeling and multi-objective optimization of a photovoltaic-thermal based multigeneration system.

Degree: 2015, University of Ontario Institute of Technology

URL: http://hdl.handle.net/10155/612

► In this thesis, a novel multi generation integrated system is introduced, analyzed and optimized. It consists of GaAs based PV (Photo-Voltaic) arrays connected in series.… (more)

▼ In this thesis, a novel multi generation integrated system is introduced, analyzed and optimized. It consists of GaAs based PV (Photo-Voltaic) arrays connected in series. Light is being concentrated on those arrays using lenses or mirrors. Concentrated light increases the cell temperature significantly. The cell is cooled down using a heat transfer fluid. This heat is being transferred to an organic Rankine cycle which not only produces electricity but also produces hot water for domestic applications. The organic Rankine cycle is also coupled with quadruple ammonia water absorption chiller. A part of the net electricity is used a PEM electrolyzer which produces hydrogen. So, using a single heat source, four useful commodities are produced, namely electricity, hot water, cooling, and hydrogen. An integrated thermal model is developed to analyze this system. Five parameters, namely pressure in primary loop, pressure and temperature of organic Rankine cycle, pressure and temperature of ammonia water chiller system are varied in order to investigate their effects on energy and exergy efficiencies, cost of electricity, enviro economic parameter and on different exergoenvironmental factors. The results indicate that the PV array should be tilted at 30?? this will give maximum radiation intensity on the surface of PV array. I-V (Current and Volt) curves shows that increasing the radiation intensity increases both the current and voltage. For sake of analysis, the system is developed for Toronto, ON, Canada. At a concentration factor of 15 in a 100 cell PV array, 196.2 V and 8 A can be achieved at a radiation intensity of 1000 W/m??. Similarly, increasing the radiation intensity can increase the cell temperature up to 700 K. The maximum calculated energy and exergy efficiencies are 46% and 40.5%, respectively. Three objective functions are developed using the data obtained from parametric study namely exergy efficiency, cost of electricity ($/kWs) and exergoenvironmental impact coefficient. These objective functions were optimized using a genetic algorithm called NSGA-II. I have a multiple solutions which is called Pareto-front. The results shows that the optimum efficiency is 38.14%, optimum cost of coefficient of electricity is 13.4 cents/kWh and optimized exergoenvironmental impact coefficient is 2.6. The multigeneration energy system discussed in this thesis and similar other alternatives (with renewable energy sources) can significantly contribute in addressing world energy needs and related challenges (e.g., human wealth, human welfare and environmental impact). Advisors/Committee Members: Rahnamayan, Shahryar, Dincer, Ibrahim.

Subjects/Keywords: Solar energy; Photovoltaics; PVT systems; Optimization; Energy

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APA (6^th Edition):

Rabbani, H. (2015). Modeling and multi-objective optimization of a photovoltaic-thermal based multigeneration system. (Thesis). University of Ontario Institute of Technology. Retrieved from http://hdl.handle.net/10155/612

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Rabbani, Hassan. “Modeling and multi-objective optimization of a photovoltaic-thermal based multigeneration system.” 2015. Thesis, University of Ontario Institute of Technology. Accessed January 24, 2021. http://hdl.handle.net/10155/612.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Rabbani, Hassan. “Modeling and multi-objective optimization of a photovoltaic-thermal based multigeneration system.” 2015. Web. 24 Jan 2021.

Vancouver:

Rabbani H. Modeling and multi-objective optimization of a photovoltaic-thermal based multigeneration system. [Internet] [Thesis]. University of Ontario Institute of Technology; 2015. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/10155/612.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Rabbani H. Modeling and multi-objective optimization of a photovoltaic-thermal based multigeneration system. [Thesis]. University of Ontario Institute of Technology; 2015. Available from: http://hdl.handle.net/10155/612

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Oklahoma State University

18. Mathema, Preety. Optimization of Integrated Renewable Energy System - Micro Grid (IRES-MG).

Degree: School of Electrical & Computer Engineering, 2011, Oklahoma State University

URL: http://hdl.handle.net/11244/10241

► Ever growing demands of increasing world population has challenged the scientific and technical communities to supply quality energy in a sustainable manner. Dependence on fossil… (more)

Subjects/Keywords: integrated renewable energy; microgrid; optimization; renewable energy

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APA (6^th Edition):

Mathema, P. (2011). Optimization of Integrated Renewable Energy System - Micro Grid (IRES-MG). (Thesis). Oklahoma State University. Retrieved from http://hdl.handle.net/11244/10241

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Mathema, Preety. “Optimization of Integrated Renewable Energy System - Micro Grid (IRES-MG).” 2011. Thesis, Oklahoma State University. Accessed January 24, 2021. http://hdl.handle.net/11244/10241.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Mathema, Preety. “Optimization of Integrated Renewable Energy System - Micro Grid (IRES-MG).” 2011. Web. 24 Jan 2021.

Vancouver:

Mathema P. Optimization of Integrated Renewable Energy System - Micro Grid (IRES-MG). [Internet] [Thesis]. Oklahoma State University; 2011. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/11244/10241.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Mathema P. Optimization of Integrated Renewable Energy System - Micro Grid (IRES-MG). [Thesis]. Oklahoma State University; 2011. Available from: http://hdl.handle.net/11244/10241

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Texas A&M University

19. Alahmadi, Hasan Ali H. A Model for Optimizing Energy Investments and Policy Under Uncertainty with Application to Saudi Arabia.

Degree: PhD, Petroleum Engineering, 2016, Texas A&M University

URL: http://hdl.handle.net/1969.1/157993

► An energy producer must determine optimal energy investment strategies in order to maximize the value of its energy portfolio. Determining optimal investment strategies is challenging.… (more)

▼ An energy producer must determine optimal energy investment strategies in order to maximize the value of its energy portfolio. Determining optimal investment strategies is challenging. One of the main challenges is the large uncertainty in many of the parameters involved in the optimization process. Existing large-scale energy models are mostly deterministic and thus have limited capability for assessing uncertainty. Modelers usually use scenario analysis to address model input uncertainty. In this research, I developed a probabilistic model for optimizing energy investments and policies from an energy producer’s perspective. The model uses a top-down approach to probabilistically forecast primary energy demand. Distributions rather than static values are used to model uncertainty in the input variables. The model can be applied to a country-level energy system. It maximizes the portfolio expected net present value (ENPV) while ensuring energy sustainability. The model was built in MSExcel® using the @RISK Palisade add-in, which is capable of modeling uncertain parameters and performing stochastic simulation optimization. The model was applied to Saudi Arabia to determine its optimum energy investment strategy, determine the value of investing in alternative energy sources, and compare deterministic and probabilistic modeling approaches. The model, given its assumptions and limitations, suggests that Saudi Arabia should keep its oil production capacity at 12.5 million barrels per day, especially in the short term. It also suggests that most of the future power-generation (electricity) demand in Saudi Arabia should be met using alternative-energy sources (nuclear, solar, and wind). Otherwise, large gas production is required to meet such demand. In addition, comparing probabilistic to deterministic model results shows that deterministic models may overestimate total portfolio ENPV and underestimate future investments needed to meet projected power demand. A primary contribution of this work is rigorously addressing uncertainty quantification in energy modeling. Building probabilistic energy models is one of the challenges facing the industry today. The model is also the first, to the best of my knowledge, that attempts to optimize Saudi Arabia’s energy portfolio using a probabilistic approach and addressing the value of investing in alternative energy sources. Advisors/Committee Members: McVay, Duane A (advisor), Gildin, Eduardo (committee member), Voneiff, George W (committee member), Mallick, Bani K (committee member).

Subjects/Keywords: Energy Optimization; Uncertainty Quantification; Probabilistic Energy Modeling; Energy Economics

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APA (6^th Edition):

Alahmadi, H. A. H. (2016). A Model for Optimizing Energy Investments and Policy Under Uncertainty with Application to Saudi Arabia. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/157993

Chicago Manual of Style (16^th Edition):

Alahmadi, Hasan Ali H. “A Model for Optimizing Energy Investments and Policy Under Uncertainty with Application to Saudi Arabia.” 2016. Doctoral Dissertation, Texas A&M University. Accessed January 24, 2021. http://hdl.handle.net/1969.1/157993.

MLA Handbook (7^th Edition):

Alahmadi, Hasan Ali H. “A Model for Optimizing Energy Investments and Policy Under Uncertainty with Application to Saudi Arabia.” 2016. Web. 24 Jan 2021.

Vancouver:

Alahmadi HAH. A Model for Optimizing Energy Investments and Policy Under Uncertainty with Application to Saudi Arabia. [Internet] [Doctoral dissertation]. Texas A&M University; 2016. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/1969.1/157993.

Council of Science Editors:

Alahmadi HAH. A Model for Optimizing Energy Investments and Policy Under Uncertainty with Application to Saudi Arabia. [Doctoral Dissertation]. Texas A&M University; 2016. Available from: http://hdl.handle.net/1969.1/157993

University of Waterloo

20. Chang, Hsiu-Chuan. Shared Community Energy Storage Allocation and Optimization.

Degree: 2019, University of Waterloo

URL: http://hdl.handle.net/10012/14628

► Distributed Energy Resources (DERs) have been playing an increasingly important role for managing households energy costs. DERs consist primarily of energy generation and storage systems… (more)

Subjects/Keywords: Community energy storage; Distributed energy resources; Smart energy community; Optimization; Allocation

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APA (6^th Edition):

Chang, H. (2019). Shared Community Energy Storage Allocation and Optimization. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/14628

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Chang, Hsiu-Chuan. “Shared Community Energy Storage Allocation and Optimization.” 2019. Thesis, University of Waterloo. Accessed January 24, 2021. http://hdl.handle.net/10012/14628.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Chang, Hsiu-Chuan. “Shared Community Energy Storage Allocation and Optimization.” 2019. Web. 24 Jan 2021.

Vancouver:

Chang H. Shared Community Energy Storage Allocation and Optimization. [Internet] [Thesis]. University of Waterloo; 2019. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/10012/14628.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Chang H. Shared Community Energy Storage Allocation and Optimization. [Thesis]. University of Waterloo; 2019. Available from: http://hdl.handle.net/10012/14628

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Arizona State University

21. Nelson, James. Model Predictive Control for Resilient Operation of Hybrid Microgrids.

Degree: Engineering, 2019, Arizona State University

URL: http://repository.asu.edu/items/55601

► This dissertation develops advanced controls for distributed energy systems and evaluates performance on technical and economic benefits. Microgrids and thermal systems are of primary focus… (more)

▼ This dissertation develops advanced controls for distributed energy systems and evaluates performance on technical and economic benefits. Microgrids and thermal systems are of primary focus with applications shown for residential, commercial, and military applications that have differing equipment, rate structures, and objectives. Controls development for residential energy heating and cooling systems implement adaptive precooling strategies and thermal energy storage, with comparisons made of each approach separately and then together with precooling and thermal energy storage. Case studies show on-peak demand and annual energy related expenses can be reduced by up to 75.6% and 23.5%, respectively, for a Building America B10 Benchmark home in Phoenix Arizona, Los Angeles California, and Kona Hawaii. Microgrids for commercial applications follow after with increased complexity. Three control methods are developed and compared including a baseline logic-based control, model predictive control, and model predictive control with ancillary service control algorithms. Case studies show that a microgrid consisting of 326 kW solar PV, 634 kW/ 634 kWh battery, and a 350 kW diesel generator can reduce on-peak demand and annual energy related expenses by 82.2% and 44.1%, respectively. Findings also show that employing a model predictive control algorithm with ancillary services can reduce operating expenses by 23.5% when compared to a logic-based algorithm. Microgrid evaluation continues with an investigation of off-grid operation and resilience for military applications. A statistical model is developed to evaluate the survivability (i.e. probability to meet critical load during an islanding event) to serve critical load out to 7 days of grid outage. Case studies compare the resilience of a generator-only microgrid consisting of 5,250 kW in generators and hybrid microgrid consisting of 2,250 kW generators, 3,450 kW / 13,800 kWh storage, and 16,479 kW solar photovoltaics. Findings show that the hybrid microgrid improves survivability by 10.0% and decreases fuel consumption by 47.8% over a 168-hour islanding event when compared to a generator-only microgrid under nominal conditions. Findings in this dissertation can increase the adoption of reliable, low cost, and low carbon distributed energy systems by improving the operational capabilities and economic benefits to a variety of customers and utilities.

Subjects/Keywords: Energy; Alternative energy; Systems science; Distributed energy resources; Microgrid; Optimization; Resilence

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APA (6^th Edition):

Nelson, J. (2019). Model Predictive Control for Resilient Operation of Hybrid Microgrids. (Doctoral Dissertation). Arizona State University. Retrieved from http://repository.asu.edu/items/55601

Chicago Manual of Style (16^th Edition):

Nelson, James. “Model Predictive Control for Resilient Operation of Hybrid Microgrids.” 2019. Doctoral Dissertation, Arizona State University. Accessed January 24, 2021. http://repository.asu.edu/items/55601.

MLA Handbook (7^th Edition):

Nelson, James. “Model Predictive Control for Resilient Operation of Hybrid Microgrids.” 2019. Web. 24 Jan 2021.

Vancouver:

Nelson J. Model Predictive Control for Resilient Operation of Hybrid Microgrids. [Internet] [Doctoral dissertation]. Arizona State University; 2019. [cited 2021 Jan 24]. Available from: http://repository.asu.edu/items/55601.

Council of Science Editors:

Nelson J. Model Predictive Control for Resilient Operation of Hybrid Microgrids. [Doctoral Dissertation]. Arizona State University; 2019. Available from: http://repository.asu.edu/items/55601

Georgia Tech

22. Alquthami, Thamer. A smart house energy management system.

Degree: PhD, Electrical and Computer Engineering, 2015, Georgia Tech

URL: http://hdl.handle.net/1853/53900

► The impact of distributed energy resources (DERs), electric vehicles/plug-in hybrid electric vehicles (EVs/PHEVs), and smart appliances on the distribution grid has been expected to be… (more)

Subjects/Keywords: Smart grid; Energy management; House energy management; Energy optimization

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APA (6^th Edition):

Alquthami, T. (2015). A smart house energy management system. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/53900

Chicago Manual of Style (16^th Edition):

Alquthami, Thamer. “A smart house energy management system.” 2015. Doctoral Dissertation, Georgia Tech. Accessed January 24, 2021. http://hdl.handle.net/1853/53900.

MLA Handbook (7^th Edition):

Alquthami, Thamer. “A smart house energy management system.” 2015. Web. 24 Jan 2021.

Vancouver:

Alquthami T. A smart house energy management system. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/1853/53900.

Council of Science Editors:

Alquthami T. A smart house energy management system. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/53900

Anna University

23. Kannan S M. Optimal energy loss estimation by locating and sizing capacitors in radial distribution system using fuzzy and optimization techniques;.

Degree: Optimal energy loss estimation by locating and sizing capacitors in radial distribution system, 2014, Anna University

URL: http://shodhganga.inflibnet.ac.in/handle/10603/23839

►

A distribution system is an interface between the bulk power newlinesystem and the consumers Among these systems radial distribution systems newlineare popular because of low… (more)

Subjects/Keywords: electrical engineering; Optimal energy; optimization techniques

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APA (6^th Edition):

M, K. S. (2014). Optimal energy loss estimation by locating and sizing capacitors in radial distribution system using fuzzy and optimization techniques;. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/23839

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

M, Kannan S. “Optimal energy loss estimation by locating and sizing capacitors in radial distribution system using fuzzy and optimization techniques;.” 2014. Thesis, Anna University. Accessed January 24, 2021. http://shodhganga.inflibnet.ac.in/handle/10603/23839.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

M, Kannan S. “Optimal energy loss estimation by locating and sizing capacitors in radial distribution system using fuzzy and optimization techniques;.” 2014. Web. 24 Jan 2021.

Vancouver:

M KS. Optimal energy loss estimation by locating and sizing capacitors in radial distribution system using fuzzy and optimization techniques;. [Internet] [Thesis]. Anna University; 2014. [cited 2021 Jan 24]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/23839.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

M KS. Optimal energy loss estimation by locating and sizing capacitors in radial distribution system using fuzzy and optimization techniques;. [Thesis]. Anna University; 2014. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/23839

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Georgia Tech

24. Athavale, Jayati Deepak. Artificial neural network based prediction and cooling energy optimization of data centers.

Degree: PhD, Mechanical Engineering, 2018, Georgia Tech

URL: http://hdl.handle.net/1853/62620

► Thermal management of data centers remains a challenge because of their ever-increasing power densities and decreasing server footprints. Current lack of dynamic control over global… (more)

▼ Thermal management of data centers remains a challenge because of their ever-increasing power densities and decreasing server footprints. Current lack of dynamic control over global provisioning and local distribution of cooling resources often result in wasteful overcooling. These trends motivate this thesis research, which focuses on the development of a reliable and energy-efficient framework for allocating cooling resources to meet thermal management requirements, while minimizing energy consumption and adverse environmental impacts. A key component of energy-efficient thermal management is real-time accurate prediction of temperature distribution in data centers. This first section of this dissertation focuses on development and comparison of four Data Driven Modeling (DDM) methods, namely Artificial Neural Networks (ANN), Support Vector Regression (SVR), Gaussian Process Regression (GPR) and Proper Orthogonal Decomposition (POD). These DDM methods were trained on datasets generated from offline Computational Fluid Dynamics/Heat Transfer (CFD/HT) simulations for real-time prediction of temperature and airflow distributions in a data center. Using CFD simulation results to train DDMs transfers computational complexity from model execution (in CFD) to model setup and development. To generate the training data, a physics-based and experimentally validated room-level CFD/HT model was developed using the commercial software Future Facilities 6Sigma Room. Another key component of the overall framework is a model to estimate the cooling power consumed by a data center. This research developed a model based on thermodynamic analyses of data center cooling equipment, as described here. Finally, development and implementation of a Genetic Algorithm (GA) based optimization framework in a data center lab is presented. The optimization framework employs an ANN based model to predict rack inlet air temperatures and a thermodynamic model to optimize cooling energy consumption. Results from a test run of 7.5 hours in the Data Center Laboratory indicate that implementing this optimization framework for dynamic provisioning of cooling resources reduces cooling power consumption by 20% compared with baseline operation without this optimization. Advisors/Committee Members: Joshi, Yogendra (advisor), Yoda, Minami (advisor), Kumar, Satish (committee member), Augenbroe, Godfried (committee member), Gavrilovska, Ada (committee member).

Subjects/Keywords: Data center thermal management; Energy optimization

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APA (6^th Edition):

Athavale, J. D. (2018). Artificial neural network based prediction and cooling energy optimization of data centers. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62620

Chicago Manual of Style (16^th Edition):

Athavale, Jayati Deepak. “Artificial neural network based prediction and cooling energy optimization of data centers.” 2018. Doctoral Dissertation, Georgia Tech. Accessed January 24, 2021. http://hdl.handle.net/1853/62620.

MLA Handbook (7^th Edition):

Athavale, Jayati Deepak. “Artificial neural network based prediction and cooling energy optimization of data centers.” 2018. Web. 24 Jan 2021.

Vancouver:

Athavale JD. Artificial neural network based prediction and cooling energy optimization of data centers. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/1853/62620.

Council of Science Editors:

Athavale JD. Artificial neural network based prediction and cooling energy optimization of data centers. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/62620

Anna University

25. Maheswar R. Performance analysis of an energy optimization scheme for cluster based heterogeneous sensor networks;.

Degree: energy optimization scheme for cluster based heterogeneous sensor networks, 2014, Anna University

URL: http://shodhganga.inflibnet.ac.in/handle/10603/24038

►

A Wireless Sensor Network WSN consists of a large number of newlinesensor nodes deployed over a geographical area for monitoring physical newlinephenomena like temperature humidity… (more)

Subjects/Keywords: electrical engineering; energy optimization; heterogeneous sensor

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APA (6^th Edition):

R, M. (2014). Performance analysis of an energy optimization scheme for cluster based heterogeneous sensor networks;. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/24038

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

R, Maheswar. “Performance analysis of an energy optimization scheme for cluster based heterogeneous sensor networks;.” 2014. Thesis, Anna University. Accessed January 24, 2021. http://shodhganga.inflibnet.ac.in/handle/10603/24038.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

R, Maheswar. “Performance analysis of an energy optimization scheme for cluster based heterogeneous sensor networks;.” 2014. Web. 24 Jan 2021.

Vancouver:

R M. Performance analysis of an energy optimization scheme for cluster based heterogeneous sensor networks;. [Internet] [Thesis]. Anna University; 2014. [cited 2021 Jan 24]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/24038.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

R M. Performance analysis of an energy optimization scheme for cluster based heterogeneous sensor networks;. [Thesis]. Anna University; 2014. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/24038

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Texas A&M University

26. Haider, Sajjad. Energy Security and Resiliency for the Texas National Guard.

Degree: MS, Energy, 2018, Texas A&M University

URL: http://hdl.handle.net/1969.1/174148

► The Texas Military Department (TMD) faces energy security issues due to the dependency of electricity from the grid that can be disrupted in case of… (more)

Subjects/Keywords: Energy; resilience; micro-grid; renewable; optimization

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APA (6^th Edition):

Haider, S. (2018). Energy Security and Resiliency for the Texas National Guard. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/174148

Chicago Manual of Style (16^th Edition):

Haider, Sajjad. “Energy Security and Resiliency for the Texas National Guard.” 2018. Masters Thesis, Texas A&M University. Accessed January 24, 2021. http://hdl.handle.net/1969.1/174148.

MLA Handbook (7^th Edition):

Haider, Sajjad. “Energy Security and Resiliency for the Texas National Guard.” 2018. Web. 24 Jan 2021.

Vancouver:

Haider S. Energy Security and Resiliency for the Texas National Guard. [Internet] [Masters thesis]. Texas A&M University; 2018. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/1969.1/174148.

Council of Science Editors:

Haider S. Energy Security and Resiliency for the Texas National Guard. [Masters Thesis]. Texas A&M University; 2018. Available from: http://hdl.handle.net/1969.1/174148

Penn State University

27. Shahriari, Mehdi. Spatial and Temporal Analysis of Renewable Power Generation Portfolios.

Degree: 2018, Penn State University

URL: https://submit-etda.libraries.psu.edu/catalog/15201mys5724

► The increase in renewable energy nameplate capacity has resulted in significant rise in net electricity generation from renewable sources. This increased renewable power penetration results… (more)

▼ The increase in renewable energy nameplate capacity has resulted in significant rise in net electricity generation from renewable sources. This increased renewable power penetration results in higher renewable integration cost. Since renewable generation technologies are weather dependent and their output cannot be predicted without uncertainty, the system operator needs to hold a larger portfolio of back-up power to maintain system reliability. One of the most common methods to address this drawback, is to spread wind turbines over space which tends to reduce output variability; this happens as distance between the turbines increases, the correlation between them decreases. In this study we are interested in studying the variability of interconnected wind farms over different spatial and temporal scales. The focus is mainly on analyzing the benefits of aggregation of wind generators over multiple spatial and temporal scales. We will also study the benefits of hybrid wind and solar systems and quantify the benefits of such systems. First, we incorporate a variance minimizing algorithm that sequentially connects wind farms. Our aim is to find the relationship between geographical scale and variance minimizing number of wind farms over different temporal scales. Our results show that the number of wind farms required to achieve minimum output volatility grows with spatial scale of aggregation. Further, we find that optimizing wind farm deployment to achieve output variance minimization over one-time scale does not imply minimizing output variance over other time scales. Further, we use the mean variance portfolio (MVP) theory to create optimal portfolios of wind and solar generators over various spatial and temporal scales. Our results indicate that using MVP will increase wind and solar capacity value. We observed that adding solar to wind portfolios will increase the capacity value of the portfolio and decrease portfolio risk. Creating portfolios in larger geographic areas and in regions with better renewable resources will decrease portfolio risk. Finally, we study the capacity value of wind and solar resources in electricity capacity markets. We consider different policy structures and analyze their benefits and shortcomings. A new measure is introduced that considers the spatial variability of wind and solar generators and has the potential to increase system reliability and generators’ revenue from capacity markets. Our results indicate that the capacity value of renewable generation technologies varies over space and time. We then use a brute force optimization method to explore revenue opportunities for wind and solar generators in electricity capacity market. Advisors/Committee Members: Seth Adam Blumsack, Dissertation Advisor/Co-Advisor, Seth Adam Blumsack, Committee Chair/Co-Chair, Guido Cervone, Committee Member, Jeffrey Brownson, Committee Member, Susan W Stewart, Outside Member.

Subjects/Keywords: Renewable Energy; Electricity Market; Portfolio Optimization

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APA (6^th Edition):

Shahriari, M. (2018). Spatial and Temporal Analysis of Renewable Power Generation Portfolios. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/15201mys5724

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Shahriari, Mehdi. “Spatial and Temporal Analysis of Renewable Power Generation Portfolios.” 2018. Thesis, Penn State University. Accessed January 24, 2021. https://submit-etda.libraries.psu.edu/catalog/15201mys5724.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Shahriari, Mehdi. “Spatial and Temporal Analysis of Renewable Power Generation Portfolios.” 2018. Web. 24 Jan 2021.

Vancouver:

Shahriari M. Spatial and Temporal Analysis of Renewable Power Generation Portfolios. [Internet] [Thesis]. Penn State University; 2018. [cited 2021 Jan 24]. Available from: https://submit-etda.libraries.psu.edu/catalog/15201mys5724.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Shahriari M. Spatial and Temporal Analysis of Renewable Power Generation Portfolios. [Thesis]. Penn State University; 2018. Available from: https://submit-etda.libraries.psu.edu/catalog/15201mys5724

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Penn State University

28. Yang, Yi. Energy Optimization for Wireless Communications on Mobile Devices.

Degree: 2018, Penn State University

URL: https://submit-etda.libraries.psu.edu/catalog/14989yzy123

► Mobile devices such as smartphones and smartwatches are becoming increasingly popular accompanied with a wide range of apps. Those apps usually require data communications through… (more)

▼ Mobile devices such as smartphones and smartwatches are becoming increasingly popular accompanied with a wide range of apps. Those apps usually require data communications through wireless interfaces, which will drain the battery quickly. Thus, it is of great value to characterize the energy consumption of wireless communications and propose energy saving solutions. The specific goal of this dissertation is to optimize the energy consumption of wireless communications on mobile devices. Specifically, this dissertation has four foci. First, we propose network quality aware prefetching algorithms to save energy for in-app advertising. The cellular interface on smartphones continues to consume a large amount of energy after a data transmission (referred to as the {\em long tail problem}). Then periodically fetching ads through the cellular network may lead to significant battery drain on smartphones. To reduce the tail energy, we can predict the number of ads needed in the future and then prefetch those ads together. However, prefetching unnecessary ads may waste both energy and cellular bandwidth, and this problem becomes worse when the network quality is poor. To solve this problem, we propose network quality aware prefetching algorithms. We first design a prediction algorithm which generates a set of prefetching options with various probabilities, and then we propose two prefetching algorithms to select the best prefetching option by considering the effect of network quality. Second, we generalize the prefetching problem, where the goal is to find a prefetching schedule that minimizes the energy consumption of the data transmissions under the current network condition. To solve the formulated nonlinear optimization problem, we first propose a greedy algorithm, and then propose a discrete algorithm with better performance. Third, we consider the context information when offloading tasks for wearable devices. Considering the low energy consumption of the Bluetooth data transmissions, wearable devices usually offload computationally intensive tasks to the connected smartphone via Bluetooth. However, existing smartphones cannot properly allocate CPU resources to these offloaded tasks due to lack of context information, resulting in either energy waste on smartphones or high interaction latency on wearable devices. To address this issue, we propose a context-aware task offloading framework, in which offloaded tasks can be properly executed on the smartphone or further offloaded to the cloud based on their context, aiming to achieve a balance between good user experience on wearable devices and energy saving on the smartphone. Finally, we characterize and optimize Bluetooth energy consumption on smartwatches. Bluetooth is used for data communications between smartwatches and smartphones, but its energy consumption has been rarely studied. To solve the problem, we first establish the Bluetooth power model and then we perform an in-depth investigation of the background data transfers on smartwatches. We found that those… Advisors/Committee Members: Guohong Cao, Dissertation Advisor/Co-Advisor, Guohong Cao, Committee Chair/Co-Chair, George Kesidis, Committee Member, Sencun Zhu, Committee Member, Dinghao Wu, Outside Member.

Subjects/Keywords: Wireless network; Energy optimization; Mobile devices

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APA (6^th Edition):

Yang, Y. (2018). Energy Optimization for Wireless Communications on Mobile Devices. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/14989yzy123

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Yang, Yi. “Energy Optimization for Wireless Communications on Mobile Devices.” 2018. Thesis, Penn State University. Accessed January 24, 2021. https://submit-etda.libraries.psu.edu/catalog/14989yzy123.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Yang, Yi. “Energy Optimization for Wireless Communications on Mobile Devices.” 2018. Web. 24 Jan 2021.

Vancouver:

Yang Y. Energy Optimization for Wireless Communications on Mobile Devices. [Internet] [Thesis]. Penn State University; 2018. [cited 2021 Jan 24]. Available from: https://submit-etda.libraries.psu.edu/catalog/14989yzy123.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Yang Y. Energy Optimization for Wireless Communications on Mobile Devices. [Thesis]. Penn State University; 2018. Available from: https://submit-etda.libraries.psu.edu/catalog/14989yzy123

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

McMaster University

29. Vu, Anh-Duy. Software Approaches to Optimize Energy Consumption for a Team of Distributed Autonomous Mobile Robots.

Degree: 2019, McMaster University

URL: http://hdl.handle.net/11375/24839

► In recent years, we have seen the applications of distributed autonomous mobile robots (DAMRs) in a broad spectrum of areas like search and rescue, disaster… (more)

▼ In recent years, we have seen the applications of distributed autonomous mobile robots (DAMRs) in a broad spectrum of areas like search and rescue, disaster management, warehouse, and delivery systems. Although each type of systems employing DAMRs has its specific challenges, they are all limited by energy since the robots are powered by batteries which have not advanced in decades. This motivates the development of energy efficiency for such systems. Although there has been research on optimizing energy for robotic systems, their approaches are from low-level (e.g., mechanic, system control, or avionic) perspectives. They, therefore, are limited to a specific type of robots and not easily adjusted to apply for different types of robots. Moreover, there is a lack of work studying the problem from a software perspective and abstraction. In this thesis, we tackle the problem from a software perspective and are particularly interested in DAMR systems in which a team of networked robots navigating in a physical environment and acting in concert to accomplish a common goal. Also, the primary focus of our work is to design schedules (or plans) for the robots so that they can achieve their goal while spending as little energy as possible. To this end, we study the problem in three different contexts: - Managing reliability and energy consumption tradeoff. That is, we propose that robots verify computational results of one another to increase the corroboration of outputs of our DAMR systems. However, this new feature requires robots to do additional tasks and consume more energy. Thus, we propose approaches to reach a balance between energy consumption and the reliability of results obtained by our DAMR systems. - Extending the operational time of robots. We first propose that our DAMR systems should employ charging stations where robots can come to recharge their batteries. Then, we aim to design schedules for the robots so that they can finish all their tasks while consuming as little energy and time (including the time spent for recharging) as possible. Moreover, we model the working space by a connected (possibly incomplete) graph to make the problem more practical. - Coping with environmental changes. This path planning problem takes into account not only energy limits but also changes in the physical environment, which may result in overheads (i.e., additional time and energy) that robots incur while doing their tasks. To tackle the problem from a software perspective, we first utilize Gaussian Process and Polynomial Regression to model disturbances and energy consumption, respectively, then proposed techniques to generate plans and adjust them when robots detect environmental changes. For each problem, we give a formal description, a transformation to integer (linear) programming, online algorithms, and an online algorithm. Moreover, we also rigorously analyze the proposed techniques by conducting simulations and experiments in a real network of unmanned aerial vehicles… Advisors/Committee Members: Karakostas, George, Computing and Software.

Subjects/Keywords: Multi-robot systems; Optimization; Energy consumption

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Vu, A. (2019). Software Approaches to Optimize Energy Consumption for a Team of Distributed Autonomous Mobile Robots. (Thesis). McMaster University. Retrieved from http://hdl.handle.net/11375/24839

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Vu, Anh-Duy. “Software Approaches to Optimize Energy Consumption for a Team of Distributed Autonomous Mobile Robots.” 2019. Thesis, McMaster University. Accessed January 24, 2021. http://hdl.handle.net/11375/24839.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Vu, Anh-Duy. “Software Approaches to Optimize Energy Consumption for a Team of Distributed Autonomous Mobile Robots.” 2019. Web. 24 Jan 2021.

Vancouver:

Vu A. Software Approaches to Optimize Energy Consumption for a Team of Distributed Autonomous Mobile Robots. [Internet] [Thesis]. McMaster University; 2019. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/11375/24839.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Vu A. Software Approaches to Optimize Energy Consumption for a Team of Distributed Autonomous Mobile Robots. [Thesis]. McMaster University; 2019. Available from: http://hdl.handle.net/11375/24839

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Brigham Young University

30. Wilcox, David Luke. Packing Virtual Machines onto Servers.

Degree: MS, 2010, Brigham Young University

URL: https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=3797&context=etd

► Data centers consume a significant amount of energy. This problem is aggravated by the fact that most servers and desktops are underutilized when powered on,… (more)

Subjects/Keywords: virtualization; optimization; energy; genetic algorithm; Computer Sciences

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Wilcox, D. L. (2010). Packing Virtual Machines onto Servers. (Masters Thesis). Brigham Young University. Retrieved from https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=3797&context=etd

Chicago Manual of Style (16^th Edition):

Wilcox, David Luke. “Packing Virtual Machines onto Servers.” 2010. Masters Thesis, Brigham Young University. Accessed January 24, 2021. https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=3797&context=etd.

MLA Handbook (7^th Edition):

Wilcox, David Luke. “Packing Virtual Machines onto Servers.” 2010. Web. 24 Jan 2021.

Vancouver:

Wilcox DL. Packing Virtual Machines onto Servers. [Internet] [Masters thesis]. Brigham Young University; 2010. [cited 2021 Jan 24]. Available from: https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=3797&context=etd.

Council of Science Editors:

Wilcox DL. Packing Virtual Machines onto Servers. [Masters Thesis]. Brigham Young University; 2010. Available from: https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=3797&context=etd

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